Machine learning models aimed at identifying risk factors for reducing morbidity and mortality still need to consider confounding related to calendar time variations

Abstract excerpt

Machine learning models applied to health data may help health professionals to prioritize resources by identifying risk factors that may reduce morbidity and mortality. However, many novel machine learning papers on this topic neither account for nor discuss biases due to calendar time variations. Often, efforts to account for calendar time (among other confounders) are necessary since patterns in health data – e...

Topics

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• Body Mass Index
• Disease Progression
• Forecasting
• Models, Statistical
• Neural Networks, Computer
• Phenotype
• Risk Assessment
• Risk Factors

Identifiers and source

Literature Corpus work

e3b3fe5c-2d91-5ed7-981c-ed1bb10f2043

DOI

10.1101/2022.05.24.22275482